permMclustGene {scDD} | R Documentation

## permMclustGene

### Description

Function to obtain bayes factor for all permutations of one gene (not parallelized; to be used when parallelizing over Genes)

### Usage

    permMclustGene(y, adjust.perms, nperms, condition, remove.zeroes = TRUE,
      log.transf = TRUE, restrict = TRUE, alpha, m0, s0, a0, b0, C, ref,
      min.size)

### Arguments

`y` | Numeric data vector for one gene
`adjust.perms` | Logical indicating whether or not to adjust the permutation tests for the sample detection rate (proportion of nonzero values). If true, the residuals of a linear model adjusted for detection rate are permuted, and new fitted values are obtained using these residuals.
`nperms` | Number of permutations of residuals to evaulate
`condition` | A character object that contains the name of the column in `colData` that represents the biological group or condition of interest (e.g. treatment versus control). Note that this variable should only contain two possible values since `scDD` can currently only handle two-group comparisons. The default option assumes that there is a column named "condition" that contains this variable.
`remove.zeroes` | Logical indicating whether zeroes need to be removed from `y`
`log.transf` | Logical indicating whether the data is in the raw scale (if so, will be log-transformed)
`restrict` | Logical indicating whether to perform restricted Mclust clustering where close-together clusters are joined.
`alpha` | Value for the Dirichlet concentration parameter
`m0` | Prior mean value for generating distribution of cluster means
`s0` | Prior precision value for generating distribution of cluster means
`a0` | Prior shape parameter value for the generating distribution of cluster precision
`b0` | Prior scale parameter value for the generating distribution of cluster precision
`C` | Matrix of confounder variables, where there is one row for each sample and one column for each covariate.
`ref` | one of two possible values in condition; represents the referent category.
`min.size` | a positive integer that specifies the minimum size of a cluster (number of cells) for it to be used during the classification step. Any clusters containing fewer than `min.size` cells will be considered an outlier cluster and ignored in the classfication algorithm. The default value is three.

### Details

Obtains bayes factor for data vector `y` representing one gene

### Value

Bayes factor numerator for the current permutation

### References

Korthauer KD, Chu LF, Newton MA, Li Y, Thomson J, Stewart R, Kendziorski C. A statistical approach for identifying differential distributions in single-cell RNA-seq experiments. Genome Biology. 2016 Oct 25;17(1):222. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1077-y

[Package scDD version 1.8.0 Index]